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app.py

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+import gradio as gr
+from transformers import AutoModel, AutoProcessor
+from PIL import Image
+import torch
+import io
+import json
+
+# Load the LayoutLMv3 model and processor
+
+
+def load_model():
+    processor = AutoProcessor.from_pretrained(
+        "microsoft/layoutlmv3-base", apply_ocr=True)
+    model = AutoModel.from_pretrained("microsoft/layoutlmv3-base")
+    return processor, model
+
+
+processor, model = load_model()
+
+# Function to process the uploaded image
+
+
+def process_document(image):
+    try:
+        # Convert Gradio image input to PIL Image
+        image = Image.frombytes("RGB", image.size, image.rgb).convert("RGB")
+
+        # Preprocess the image with the processor
+        encoding = processor(image, return_tensors="pt")
+
+        # Run the model
+        with torch.no_grad():
+            outputs = model(**encoding)
+
+        # Extract logits or embeddings (modify based on your task)
+        logits = outputs.logits if hasattr(
+            outputs, 'logits') else outputs.last_hidden_state
+
+        # Placeholder result; customize based on your task (e.g., token classification, text extraction)
+        result = {
+            "status": "success",
+            "model_output_shape": str(logits.shape),
+            "message": "Document processed successfully. Customize this section for specific outputs."
+        }
+
+        return image, json.dumps(result, indent=2)
+
+    except Exception as e:
+        return image, f"Error processing document: {str(e)}"
+
+
+# Gradio Interface
+with gr.Blocks(title="Document Analysis with LayoutLMv3") as demo:
+    gr.Markdown("# Document Analysis with LayoutLMv3")
+    gr.Markdown(
+        "Upload a document image (PNG, JPG, JPEG) to analyze its layout and extract text.")
+
+    with gr.Row():
+        with gr.Column():
+            image_input = gr.Image(type="pil", label="Upload Document Image")
+            submit_button = gr.Button("Process Document")
+        with gr.Column():
+            image_output = gr.Image(label="Uploaded Image")
+            text_output = gr.Textbox(label="Analysis Results")
+
+    submit_button.click(
+        fn=process_document,
+        inputs=image_input,
+        outputs=[image_output, text_output]
+    )
+
+    gr.Markdown("""
+    ### Instructions
+    1. Upload a document image (PNG, JPG, or JPEG).
+    2. Click "Process Document" to analyze the image.
+    3. View the results in the output section.
+    4. This is a basic demo; customize the output processing for specific tasks (e.g., text extraction, layout analysis).
+    """)
+
+# Launch the Gradio app
+demo.launch()

requirements.txt

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+transformers
+torch
+gradio
+pillow